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Abstract Activity and autonomous motion are fundamental aspects of many living and engineering systems. Here, the scale of biological agents covers a wide range, from nanomotors, cytoskeleton, and cells, to insects, fish, birds, and people. Inspired by biological active systems, various types of autonomous synthetic nano- and micromachines have been designed, which provide the basis for multifunctional, highly responsive, intelligent active materials. A major challenge for understanding and designing active matter is their inherent non-equilibrium nature due to persistent energy consumption, which invalidates equilibrium concepts such as free energy, detailed balance, and time-reversal symmetry. Furthermore, interactions in ensembles of active agents are often non-additive and non-reciprocal. An important aspect of biological agents is their ability to sense the environment, process this information, and adjust their motion accordingly. It is an important goal for the engineering of micro-robotic systems to achieve similar functionality. With many fundamental properties of motile active matter now reasonably well understood and under control, the ground is prepared for the study of physical aspects and mechanisms of motion in complex environments, of the behavior of systems with new physical features like chirality, of the development of novel micromachines and microbots, of the emergent collective behavior and swarming of intelligent self-propelled particles, and of particular features of microbial systems. The vast complexity of phenomena and mechanisms involved in the self-organization and dynamics of motile active matter poses major challenges, which can only be addressed by a truly interdisciplinary effort involving scientists from biology, chemistry, ecology, engineering, mathematics, and physics. The 2024 motile active matter roadmap of Journal of Physics: Condensed Matter reviews the current state of the art of the field and provides guidance for further progress in this fascinating research area. 

Metachronal motions are ubiquitous in terrestrial and aquatic organisms and have attracted substantial attention in engineering for their potential applications. Hard‐magnetic soft materials are shown to provide new opportunities for metachronal wave‐modulated robotic locomotion by multi‐agent active morphing in response to external magnetic fields. However, the design and optimization of such magnetic soft robots can be complex, and the fabrication and magnetization processes are often delicate and time‐consuming. Herein, a computational model is developed that integrates granular models into a magnetic–lattice model, both of which are implemented in the highly efficient parallel computing platform large‐scale atomic/molecular massively parallel simulator (LAMMPS). The simulations accurately reproduce the deformation of single cilium, the metachronal wave motion of multiple cilia, and the crawling and rolling locomotion of magnetic cilia soft robots. Furthermore, the simulations provide insight into the spatial and temporal variation of friction forces and trajectories of cilia tips. The results contribute to the understanding of metachronal wave‐modulated locomotion and potential applications in the field of soft robotics and biomimetic engineering. The developed model also provides a versatile computational framework for simulating the movement of magnetic soft robots in realistic environments and has the potential to guide the design, optimization, and customization of these systems.